Resolving Small‐Scale Forest Snow Patterns Using an Energy Balance Snow Model With a One‐Layer Canopy. Issue 1 (14th January 2020)

• Record Type: Journal Article
• Authors: Mazzotti, Giulia; Essery, Richard; Moeser, C. David; Jonas, Tobias
• Is Part Of: Water resources research. Volume 56:Issue 1(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-01-14
• Subjects: forest snow -- snow cover models -- snow energy balance -- forest canopy structure -- snow hydrology -- land surface modeling; Hydrology -- Periodicals; 333.91
• DOI: 10.1029/2019WR026129
• Languages: English
• ISSNs: 0043-1397

Abstract

Abstract: Modeling spatiotemporal dynamics of snow in forests is challenging, as involved processes are strongly dependent on small‐scale canopy properties. In this study, we explore how local canopy structure information can be integrated in a medium‐complexity energy balance snow model to replicate observed snow patterns at very high spatial resolutions. Snow depth distributions simulated with the Flexible Snow Model (FSM2) were tested against extensive experimental data acquired in discontinuous subalpine forest stands in Eastern Switzerland over three winters. While the default canopy implementation in FSM2 fails to capture the observed snow depth variability, performance is considerably improved when local canopy cover fraction and hemispherical sky view fraction are additionally accounted for (30% reduction in root mean square error). However, realistic snow depth distribution patterns throughout the season are only achieved if effective temperatures of near and distant canopy elements are discerned and if a mechanism to mimic preferential deposition of snow in canopy gaps is included. We demonstrate that by diversifying the canopy structure input in order to reflect respective portions of the canopy relevant to different processes, even a simple model based on widely used process parameterizations and canopy metrics can be applied for high‐resolution simulations of the sub‐canopy snow cover with just a few modifications. The presented approaches could be implemented in commonly used land surface models, allowing upscaling experiments and development of sub‐grid parameterizations without necessitating complex high‐resolution models. Key Points: Alternative strategies to represent fine‐scale forest canopy structure within a standard energy balance snow model were tested Only canopy representations that distinguish between near and distant canopy elements simulated realistic snow distributions The proposed approach uses standard canopy parameters only and can thus be transferred to other model frameworks